Currently Active Research Projects

Our Research

Browse below to learn more about our faculty's research.

Social Determinants in Cancer Epidemiology

Drs. Brian Joyce and Adam Murphy are partnering on a study of social determinants of health and prostate cancer in Chicago communities. Prostate cancer is both more common and more lethal, and diagnosed younger and at a more advanced stage, in Black men compared to White men. These racial disparities may be related to neighborhood characteristics, moving beyond socioeconomic status to include food access, exposure to crime/violence, built environment/walkability, and segregation/racial composition. Through a process called geocoding these data can be linked to the home addresses of study participants, enabling us to study both neighborhood and individual characteristics in models to try and predict prostate cancer. Drs. Joyce and Murphy ultimately hope to design a new index of these social risk factors that can be used to predict prostate cancer, particularly in high-risk Black men, and link it to molecular biomarkers that can then be used for earlier diagnosis.

Methodology Development

A Professor in the Department of Statistics and Data Science, Dr. Hongmei Jiang's research focuses on developing statistical methodologies and computational algorithms to analyze and understand massive amounts of -omics (e.g., genomics, epigenomics, and metagenomics) data, multiple comparisons and multiple tests, and longitudinal data analysis. In the past few years, she has been primarily working on microbiome data analysis including identification and quantification of microbial species and gene functions, tests of differentially abundant OTUs or species, and microbial interaction networks. She has been collaborating with Dr. Hou's group to study cell-type-specific DNA methylation biomarkers using methylation data generated from white blood cells.

Epigenetics as Potential Pathways linking Risk Factors and Chronic Diseases

Dr. Tao Gao is engaged in research focusing on the epigenetic and molecular mechanisms as potential functional pathways linking environmental and lifestyle factors and the development of chronic diseases including cancer and cardiovascular diseases. Several epigenetic biomarkers using weighted averages of methylation levels at specific loci (CpG sites) have been proposed to measure “epigenetic age” and shown to prospectively associate with age-related diseases. One of Dr. Gao’s studies on plasma lipid profiles and epigenetic aging found that high triglycerides and low high-density lipoprotein cholesterol in early adulthood are associated with accelerated epigenetic aging by midlife. Dr. Gao is also investigating the association between dietary patterns including three dietary quality indexes (Healthy Eating Index (HEI), Mediterranean diet (MedDiet) score, and the empirical dietary inflammatory pattern (EDIP) score) and epigenetic aging.

Omics Biomarkers in Prediction of Phenotypes and Diseases

Omics-based biomarkers include genes (genomics), DNA methylation (epigenetics), messenger RNA and microRNAs (transcriptomics), mitochondrial DNA, and proteins (proteomics). These factors not only play a significant role in advancing understanding of the etiology and biological processes of diseases but also have great potential to help detect diseases at an early stage, which improves prevention and diagnosis. Doctoral student Yishu Qu has been working on identifying omics biomarkers to predict phenotypes and chronic diseases, as well as developing novel approaches to integrate multi-omics biomarkers. She previously conducted a study that identified a blood DNA methylation-based biomarker associated with higher hepatic fat and imaging-diagnosed non-alcoholic fatty liver disease. She is also investigating genetic variations, DNA methylation patterns, and mitochondrial heteroplasmy to predict lipid profiles as well as predict the risk of having dyslipidemia and cardiovascular diseases.